Optical (i.e., transport) networks and the like (e.g., wavelength division multiplexing (WDM), Synchronous Optical Network (SONET), Synchronous Digital Hierarchy (SDH), Optical Transport Network (OTN), Ethernet, and the like) at various layers are deploying control plane systems and methods. Control plane systems and methods provide automatic allocation of network resources in an end-to-end manner. Example control planes may include Automatically Switched Optical Network (ASON) as defined in G.8080/Y.1304, Architecture for the automatically switched optical network (ASON) (February/2005), the contents of which are herein incorporated by reference; Generalized Multi-Protocol Label Switching (GMPLS) Architecture as defined in Request for Comments (RFC): 3945 (October/2004) and the like, the contents of which are herein incorporated by reference; Optical Signaling and Routing Protocol (OSRP) from Ciena Corporation which is an optical signaling and routing protocol similar to PNNI (Private Network-to-Network Interface) and MPLS; or any other type control plane for controlling network elements at multiple layers, and establishing connections there between.
The GMPLS, ASON, etc. standards are driving increasing levels of dynamic optical network reconfigurability. Optical signal propagation is an inherently analog process, and monitoring analog network performance is critical to dynamic reconfigurability. Both optical network design and reconfiguration require the use of optical path computation software that computes expected signal performance based on specific network physical characteristics. An example of such path computation software is the Path Computation Element (PCE) currently under consideration in the IETF. These must still be validated against field measurements, as there are large uncertainties in the optical fiber and installed equipment as well as possible aging errors. Networks may have wavelengths with several technology generations supporting a variety of data rates, modulation formats, and the like.
The current state of the art in deployed networks is limited to three types of measurements. First, existing channels provide a measure of both pre-corrected and post-corrected Forward Error Correction (FEC) error counts. These are only available for specific lightpaths, where channels with embedded FEC are already installed and operational. Further, pre-FEC bit error rate (BER) is only accurate at high values. At lower values of BER, the counts only provide an upper bound measurement due to the presence of dynamic control algorithms, which stop working once a specific bound is reached. Finally, no information is provided that can be used to predict the performance of channels with a different bit rate and modulation format.
Second, channel power levels are available at various points in the system, either as an aggregate total or for individual channels as at Optical Channel Monitor (OCM) points. These provide some indication of the overall system health but can say very little about specific channel performance or about path suitability for additional channels. Third, some recent monitors have added Optical Signal-to-Noise Ratio (OSNR) measurement capability, which provides an indication of one or more major optical signal impairment mechanisms.
While some signal quality measurement approaches exist, they do not provide sufficient information to accurately estimate new channel performance or to validate the accuracy of the path computation calculation. What is missing is the ability to extract the following:                More accurate OSNR measurement;        Estimation for residual Chromatic Dispersion;        Estimation for Polarization Dependent Loss;        Estimation for Polarization Mode Dispersion;        Estimation for inter-channel nonlinear effects, such as Cross-Phase Modulation (XPM) and Four Wave Mixing (FWM);        Estimation for intra-channel nonlinear effects, such as Self-Phase Modulation (SPM), iXPM, iFWM; and        Estimation for possible bandwidth narrowing due to in-line optical filtering (for example, Optical Add-Drop Module (OADM) filters).        
With respect to Optical Service Channels (OSCs), conventional OSCs use fixed wavelength intensity modulated direct detection (IMDD) transponders in an out-of-band wavelength. Feedback on performance data in conventional systems use coherent transponders to glean some link performance information on a path-by-path basis; however, the majority of link characterization is done before the system gets deployed. Conventional optical service channels offer only limited line characterization with the main purpose providing communication between network components.
As described herein, link characterization in conventional systems includes major cost and complexity in designing and deploying optical networks. The process of producing link budgets (optical performance) involves collecting data on the network, and propagation simulation. This is a lengthy, expensive, time consuming process. The main limitation of this process is that data is only gathered once in the lifetime of the system—before it is even deployed. Normally, since OSC's have been traditionally IMDD receivers, there is the need to filter the output of each span so that only the OSC wavelength range is present on the OSC receiver. Since this is the case, it is normally the practice to use an out of band wavelength which is not amplified by the EDFAs in the system. This saves bandwidth for data-bearing traffic, but limits the usefulness of the OSC measurements since it cannot measure the ASE generated by the amplifiers themselves. Therefore, conventional OSCs offer some direct characterization which is limited to loss, latency and with a coarse precision, chromatic dispersion.
Other characteristics of the line system must be calculated indirectly from these measurements and the one-time, start-of-life fiber characterization data using detailed knowledge of the system design, for example, the noise figure of the amplifiers, user knowledge of the fiber type, etc. Active feedback on performance data in current systems has been suggested using coherent transponders to glean some link performance information. However, this information is available only for in-service light paths, making it difficult or impossible to locate the source of any particular effect or degradation within those paths, and results in a complete lack of information on paths which are not currently in use.